5 citations · 12 across the 7 of their papers we have counts for
7 papers
Predicting the Factuality of Reporting of News Media Using Observations About User Attention in Their YouTube Channels
Krasimira Bozhanova, Yoan Dinkov, Ivan Koychev +3
We propose a novel framework for predicting the factuality of reporting of news media outlets by studying the user attention cycles in their YouTube channels. In particular, we des…
A Neighbourhood Framework for Resource-Lean Content Flagging
Sheikh Muhammad Sarwar, Dimitrina Zlatkova, Momchil Hardalov +3
We propose a novel framework for cross-lingual content flagging with limited target-language data, which significantly outperforms prior work in terms of predictive performance. Th…
Detecting Harmful Content On Online Platforms: What Platforms Need Vs. Where Research Efforts Go
Arnav Arora, Preslav Nakov, Momchil Hardalov +8
The proliferation of harmful content on online platforms is a major societal problem, which comes in many different forms including hate speech, offensive language, bullying and ha…
EXAMS: A Multi-Subject High School Examinations Dataset for Cross-Lingual and Multilingual Question Answering
Momchil Hardalov, Todor Mihaylov, Dimitrina Zlatkova +3
We propose EXAMS -- a new benchmark dataset for cross-lingual and multilingual question answering for high school examinations. We collected more than 24,000 high-quality high scho…
What Was Written vs. Who Read It: News Media Profiling Using Text Analysis and Social Media Context
Ramy Baly, Georgi Karadzhov, Jisun An +5
Predicting the political bias and the factuality of reporting of entire news outlets are critical elements of media profiling, which is an understudied but an increasingly importan…
Predicting the Leading Political Ideology of YouTube Channels Using Acoustic, Textual, and Metadata Information
Yoan Dinkov, Ahmed Ali, Ivan Koychev +1
We address the problem of predicting the leading political ideology, i.e., left-center-right bias, for YouTube channels of news media. Previous work on the problem has focused excl…
Detecting Toxicity in News Articles: Application to Bulgarian
Yoan Dinkov, Ivan Koychev, Preslav Nakov
Online media aim for reaching ever bigger audience and for attracting ever longer attention span. This competition creates an environment that rewards sensational, fake, and toxic…